Dynamical networks from correlations
Date
2006
Authors
Aste, Tomaso
Di Matteo, Tiziana
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
The extraction of relevant and meaningful information from large streams of data has become one of the major challenges for scientists working in the field of complex systems. In particular, one of the main goals is to get information about the underlying system of interactions that leads to complex collective dynamics. In this paper, we discuss how a set of relevant interactions can be extracted from the analysis of the cross-correlation matrix. We show that an active and adaptive correlation filtering procedure can be associated to the dynamics of a network which is a sort of 'hyper-molecule' warped on a D-dimensional unitary sphere.
Description
Keywords
Keywords: Correlation methods; Data processing; Information retrieval; Kalman filtering; Large scale systems; Matrix algebra; Adaptive correlation filtering; Dynamical networks; Econophysics; Financial data correlations; Computer networks Complex systems; Econophysics; Financial data correlations; Networks; Time series analysis
Citation
Collections
Source
Physica A: Statistical mechanics and its applications
Type
Journal article
Book Title
Entity type
Access Statement
License Rights
Restricted until
2037-12-31
Downloads
File
Description